Associate Data Ops Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Data and ML Ops Engineers at N1 Health are tasked with managing the broad complexity of healthcare data and scalably delivering it to end users. In this role, you will work on client-facing teams of data scientists, project managers, and expert staff to deploy our product and add new data sources to enhance our models. You'll own data specifications, schema design, data pipelines, and ML pipelines for the team, and you'll use Python, SQL, and Go to automate and scale them. As a client-facing engineer, you'll build scalable pipelines on top of our platform, think creatively about building new tools that add value, and communicate with stakeholders about how best to deploy them to drive meaningful healthcare outcomes.

Technical Requirements

• We’re looking for motivated teammates who are ready to learn and grow. If you’re passionate about what we do and don’t meet every requirement, we’d still love to hear from you.
• Bachelor’s degree or education in computer science/related field
• 0-2 years of prior software engineering experience
• Proficiency in Python and SQL, or demonstrated ability to learn new languages quickly

The Ideal Fit

• Strong written and verbal communication skills with internal and client teams
• Demonstrated ability to work on complex projects with multiple stakeholders
• Proactive team-player who takes ownership and initiative on a variety of problems
• Ability to tell a compelling and data-driven story
• Commitment to understanding the healthcare industry, including data and security requirements

What You Will Do

• Own feature engineering and data modeling to ensure data is ready for analysis
• Deploy and scale machine learning pipelines that power large scale patient programs
• Work directly with client teams to manage data SLAs, documentation, and integration
• Write well-documented and versioned code that supports repeatable work